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Maximizing Value

Big data can create significant value, but getting the most value from big data requires taking another look at your business model with new realities in mind.

Big data can generate big revenues—an average of 12% of total sales for leading companies regardless of size or industry, according to a recent survey. Since annual revenues at most of these companies exceed $1 billion, that percentage represents significant value creation.

There are many ways that big data can generate revenue, spur product and service innovation, cut costs, improve operations and business models, and monetize data. The most common area is product innovation, but the biggest gains come from business model innovation and data monetization—both of which have fundamental impact across the organization.

Advanced analytical approaches that can address the highest priority opportunities are by far the quickest path to value over the short term. This is especially true in the areas of customer management, product and marketing analytics, operation and supply chain management, enterprise functions, and risk management.

5 Big Data Best Practices for Retailers

Big data represents a huge opportunity for retailers, but it requires the right analytical capabilities and internal processes to find the value. To explore the opportunities that big data provides, retailers can take these steps:

  1. Focus on the most pressing opportunities. Don’t try to build a complete solution. Instead, determine how to fuel growth in specific ways.
  2. Start with the data you really need.  Sales, costs, promotions, space, store locations, and customer data should be connected, but only if it will drive value for the business in the near term.
  3. Bring the organization along. Include people who make daily decisions—buyers, trade planners, and others—in the analytical process. It will improve results and create buy-in to new initiatives.
  4. Translate the analysis into tangible actions for the broader organization to validate. Ultimately, big data in retail needs to help people make practical decisions faster and more easily. Recommendations should resonate with those making the daily decisions.
  5. Maintain trust. To create trust and gain access to even greater amounts of personal data, communicate transparently with consumers about how you use data and what they can expect in return.
Big Data & Advanced Analytics
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